Chemical selection for the Thyroid Validation Study coordinated by EURL ECVAM and involving EU-NETVAL laboratories_suppl3
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The aim of the Thyroid Validation Study, coordinated by EURL ECVAM and involving EU-NETVAL laboratories, was to validate selected non-animal methods for the identification of chemicals that can potentially disrupt the thyroid hormone system in humans. The validation study was organized in two parts: Part 1 was to assess method performance and develop standard operating procedures, where needed, and Part 2 was to assess the mechanistic relevance of the methods using a set of validation chemicals. This paper describes the stepwise process to select this validation set of chemicals, mainly based on extensive literature review and expert judgment elicitation to identify chemicals for which there was evidence to show their (lack of) ability to perturb the thyroid hormone signaling mechanisms or modes of action covered by the methods. A unique contribution of the study lies in its mechanistic coverage of molecular targets within the thyroid gland but also regulatory mechanisms in peripheral tissues, reflecting a multifaceted perspective on thyroid hormone action. The validation set consisted of 30 chemicals, providing a balanced representation across a broad chemical space and offering insights into the mechanistic relevance of the selected methods. Once validated, these methods will contribute to advancing the identification and evaluation of endocrine disruptors, informing regulatory decisions, and promoting alternative testing strategies. Plain language summaryThis manuscript provides important insights that will allow the progression of non-animal methods for thyroid hormone disruption and their use in the regulatory context. The selection of chemicals used in a validation study is of paramount importance and will impact on the overall performance of the methods being validated. The selection approach used is described in detail and provides a relevant and useful guide for possible future validation studies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it